Sex differences in the etiology and burden of heart failure across country income level: analysis of 204 countries and territories 1990–2019
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is a global epidemic. OBJECTIVE: To assess global sex differences in HF epidemiology across country income levels. METHODS AND RESULTS: Using Global Burden of Disease (GBD) data from 204 countries and territories 1990-2019, we assessed sex differences in HF prevalence, etiology, morbidity, and temporal trends across country sociodemographic index or gross national income. We derived age-standardized rates. Of 56.2 million (95% uncertainty interval [UI] 46.4-67.8 million) people with HF in 2019, 50.3% were females and 69.2% lived in low- and middle-income countries; age-standardized prevalence was greater in males and in high-income countries. Ischaemic and hypertensive heart disease were top causes of HF in males and females, respectively. There were 5.1 million (95% UI 3.3-7.3 million) years lived with disability, distributed equally between sexes. Between 1990 and 2019, there was an increase in HF cases, but a decrease in age-standardized rates per 100 000 in males (9.1%, from 864.2 to 785.7) and females (5.8%, from 686.0 to 646.1). High-income regions experienced a 16.0% decrease in age-standardized rates (from 877.5 to 736.8), while low-income regions experienced a 3.9% increase (from 612.1 to 636.0), largely consistent across sexes. There was a temporal increase in age-standardized HF from hypertensive, rheumatic, and calcific aortic valvular heart disease, and a decrease from ischaemic heart disease, with regional and sex differences. CONCLUSION: Age-standardized HF rates have decreased over time, with larger decreases in males than females; and with large decreases in high-income and small increases in low-income regions. Sex and regional differences offer targets for intervention.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it